Tiger on the prowl: Invasion history and spatio-temporal genetic structure of the Asian tiger mosquito Aedes albopictus (Skuse 1894) in the Indo-Pacific

Abstract

Background: Within the last century, increases in human movement and globalization of trade have facilitated the establishment of several highly invasive mosquito species in new geographic locations with concurrent major environmental, economic and health consequences. The Asian tiger mosquito, Aedes albopictus, is an extremely invasive and aggressive daytime-biting mosquito that is a major public health threat throughout its expanding range.

Methodology/principal findings: We used 13 nuclear microsatellite loci (on 911 individuals) and mitochondrial COI sequences to gain a better understanding of the historical and contemporary movements of Ae. albopictus in the Indo-Pacific region and to characterize its population structure. Approximate Bayesian computation (ABC) was employed to test competing historical routes of invasion of Ae. albopictus within the Southeast (SE) Asian/Australasian region. Our ABC results show that Ae. albopictus was most likely introduced to New Guinea via mainland Southeast Asia, before colonizing the Solomon Islands via either Papua New Guinea or SE Asia. The analysis also supported that the recent incursion into northern Australia's Torres Strait Islands was seeded chiefly from Indonesia. For the first time documented in this invasive species, we provide evidence of a recently colonized population (the Torres Strait Islands) that has undergone rapid temporal changes in its genetic makeup, which could be the result of genetic drift or represent a secondary invasion from an unknown source.

Conclusions/significance: There appears to be high spatial genetic structure and high gene flow between some geographically distant populations. The species' genetic structure in the region tends to favour a dispersal pattern driven mostly by human movements. Importantly, this study provides a more widespread sampling distribution of the species' native range, revealing more spatial population structure than previously shown. Additionally, we present the most probable invasion history of this species in the Australasian region using ABC analysis.

Fig 1. Bayesian STRUCTURE plot (K = 4) for 13 microsatellite loci for 911 samples of Aedes albopictus in the study region.

Each vertical bar in the plots represents an individual sample, where the color of the bar indicates the probability of the individual belonging to a genetic cluster. Samples are positioned on the map corresponding to the population’s location (orange dot) and are abbreviated as in Table 1. Map insets represent the following: A) Torres Strait Islands and Southern Fly Region of Papua New Guinea; B) Hawaii; C) Atlanta. Insets B and C are to scale with the main map scale. The top-left color key shows the color of clusters, as referred to in the main text.

Fig 2. Invasion scenarios of Aedes albopictus in Australasia tested using approximate Bayesian computation (ABC).

One unsampled and six sampled populations were modelled, shown as colored lines in five different invasion scenarios. Time events (t1-t7) are not to scale, but their prior distributions are displayed as the year (except t7 which is shown in years before present (ybp, present = 2015)). Changes in effective population size (N_e) are represented as differently shaded lines, where db-db4 represent the duration; narrowing lines represent population bottlenecks that were given lower N_e priors ranges; rate of admixture (ra) is also shown. All populations have samples at time = 0 (i.e. 2015) and asterisks represent additional temporal sampling of populations (i.e. for TS and PNG). The posterior probabilities of all scenarios are shown with 95% confidence intervals in square brackets; Scenario 4 was the best-fit scenario. See S3 Table for further details and posterior distributions.

Fig 3. Major mitochondrial COI haplotypes for Aedes albopictus in the Indo-Pacific, Asian and USA region, representing 92% of the 1044 individuals analyzed.

Displayed are the nine most prevalent COI haplotypes (of 52 in total) using data from ours and other studies, where each haplotype is represented as a different color and the size of the circle represents the number of individuals from a given region (which is plotted on the map). Note, the placement of circles does not correspond to the exact location of haplotypes, but represents the general region they are from; refer to S6 Table for the exact location of haplotypes and for additional haplotypes found in the region. Insets show distant regions, but are to scale with the main map: A) Madagascar and La Réunion; B) Hawaii; C) USA.